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Spatial variability in depositional reservoir quality of deep-water channel-fill and lobe depositsDOI:10.1016/j.marpetgeo.2018.07.023
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Citation for published version (APA):Bell, D., Kane, I., Ponten, A., Flint, S., Hodgson, D. M., & Barrett, B. J. (2018). Spatial variability in depositionalreservoir quality of deep-water channel-fill and lobe deposits. Marine and Petroleum Geology, 98, 97-115.https://doi.org/10.1016/j.marpetgeo.2018.07.023
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Download date:20. Mar. 2020
Spatial variability in depositional reservoir quality of deep-water channel-fill and lobe 1
deposits 2
Daniel Bell1*, Ian A. Kane1, Anna S. M. Pontén2, Stephen S. Flint3, David M. Hodgson4 and 3
Bonita J. Barrett4 4
5
1 SedRESQ, School of Earth and Environmental Sciences, University of Manchester, 6
Manchester, M13 9PL, U.K. 7
2 Equinor ASA, Research Center Rotvoll, NO-7005 Trondheim, Norway 8
3 Stratigraphy Group, School of Earth and Environmental Sciences, University of Manchester, 9
Manchester, M13 9PL, U.K. 10
4 Stratigraphy Group, School of Earth and Environment, University of Leeds, Leeds, LS2 9JT, 11
U.K 12
Email: daniel.bell-2@manchester.ac.uk 13
Keywords: deep-water sedimentology, reservoir quality, turbidites, submarine channel, submarine 14
lobe, Pyrenees, process sedimentology, sedimentary petrology 15
Abstract 16
Initial porosity and permeability in deep-water systems is controlled by primary sedimentary 17
texture and mineralogy. Therefore, understanding the sedimentary processes that control changes 18
in primary texture is critical for improved reservoir quality predictions. A well-constrained, 19
exhumed submarine lobe in the Jaca Basin, and a submarine channel-fill element in the Aínsa 20
Basin, northern Spain, were studied to characterize the depositional reservoir quality in axial to 21
marginal/fringe positions. Construction of architectural panels and strategic sampling enabled 22
analysis of the spatial changes in textural properties, and their relationship to reservoir quality 23
distribution. Samples were analysed in thin-section to establish how depositional processes 24
inferred from outcrop observations affect textural properties. Results show that high-density 25
turbidites are concentrated in lobe- and channel-axis positions and exhibit good depositional 26
reservoir quality. Lobe off-axis deposits contain high- and low-density turbidites and have 27
moderate depositional reservoir quality. Conversely, low-density turbidites dominate lobe fringe 28
and channel-margin positions and have relatively poor depositional reservoir quality. There is a 29
sharp decrease in depositional reservoir quality between the lobe off-axis and lobe fringe due to: 30
1) an abrupt increase in matrix content; 2) an abrupt decrease in sandstone amalgamation; and 3) 31
a decrease in grain-size. There is an abrupt increase in depositional reservoir quality from channel 32
margin to channel axis corresponding to: 1) an increase in total sandstone thickness and 33
amalgamation; 2) an increase in grain-size, 3) a decrease in matrix content. Rates of change of key 34
properties are up to two orders of magnitude greater between channel-fill sub-environments 35
compared to lobe sub-environments. Spatial variability in properties of discrete architectural 36
elements, and rates of changes, provides input to reservoir models during exploration, appraisal, 37
and development phases of hydrocarbon fields. 38
1.1 Introduction 39
Submarine fans represent large volumes of terrigenous sediment transported from the 40
continental shelf to the slope and basin floor (e.g. Emmel and Curray, 1983; Piper et al., 1999; 41
Talling et al., 2007; Prélat et al., 2010; Clare et al., 2014) . Modern deep-marine systems are 42
repositories for anthropogenically derived sediment and pollutants, and organic matter (e.g. Galy 43
et al., 2007; Saller et al., 2008; Hodgson, 2009; Gwiazda et al., 2015) , and buried systems form 44
reservoirs for groundwater and hydrocarbons, as well as economic accumulations of minerals (e.g. 45
Pettingill, 1998; Ruffell et al., 1998; Weimer et al., 2000; McKie et al., 2015). Consequently, 46
understanding the distribution of depositional facies and their porosity and permeability is key to 47
understanding the distribution and stability of subsurface fluids and minerals (Lien et al., 2006; 48
Porten et al., 2016; Southern et al., 2017). 49
The porosity of unconsolidated sediments is controlled by the grain-size, sorting and 50
packing of grains (Fraser, 1935; Beard and Weyl, 1973; Hirst et al., 2002; Lien et al., 2006; Njoku 51
and Pirmez, 2011; Porten et al., 2016), whereas detrital clay content, clay mineralogy, and clay 52
distribution have a strong control on permeability (e.g. Wilson, 1992; Hirst et al., 2002; Lien et al., 53
2006; Ajdukiewicz et al., 2010; Dowey et al., 2012; Porten et al., 2016) . These relationships are 54
demonstrated in terrestrial and shallow-marine deposits (e.g. Pryor, 1973; Haile et al., 2017). 55
However, the general inaccessibility of modern deep-water systems means the primary distribution 56
of their textural characteristics is less-well understood. 57
Controls on reservoir quality operate on a range of scales. At the largest-scale, sandstone 58
reservoir quality is determined by the volume of the deposit and connectivity, as elements include 59
both sand and non-sand reservoir (e.g. Kerr and Jirik, 1990; Hardage et al., 1996; Afifi, 2005; Jolley 60
et al., 2010; Kilhams et al., 2015; Lan et al., 2016). Within the sandstone portion of the reservoir, 61
‘quality’ is predominantly determined by grain-scale porosity and permeability (e.g. Fraser, 1935; 62
Marzano, 1988; Ramm and Bjørlykke, 1994; Ehrenberg, 1997; Worden et al. , 2000; Marchand et 63
al., 2015; Porten et al., 2016), which is modified by eodiagenetic and mesodiagenetic processes (e.g. 64
Ehrenberg, 1989; Pittman and Larese, 1991; Ramm and Bjørlykke, 1994; Ehrenberg, 1997; Worden 65
et al., 2000). It is recognized that the primary texture of depositional facies in deep-water 66
sandstones can also maintain a strong control even after diagenesis (Hirst et al., 2002; Lien et al., 67
2006; Njoku and Pirmez, 2011; Kilhams et al., 2012; Marchand et al., 2015; Porten et al., 2016). 68
“Depositional reservoir quality” is the initial reservoir potential of a sedimentary accumulation 69
prior to post-depositional modification (Porten et al., 2016). The type of flow that generates a 70
deposit has a strong influence on its texture (Hirst et al., 2002; Lien et al., 2006; Njoku and Pirmez, 71
2011; Kilhams et al., 2012; Porten et al., 2016; Kane et al., 2017) . Therefore, the primary texture 72
of deposits from discrete flow-types can also maintain a strong control during all stages of 73
diagenesis (Hirst et al., 2002; Lien et al., 2006; Njoku and Pirmez, 2011; Kilhams et al ., 2012; 74
Marchand et al., 2015; Porten et al., 2016). 75
76
Figure 1: A) Location of study area in Spain; B) Regional locality map showing the two studied areas; C) 77
Localities of the Gerbe channel-fill outcrops; D) Localities of Upper Broto, Lobe 1 outcrops. Image 78
sources: Esri, DeLorme, HERE, MapmyIndia, OpenStreetMap contributors. 79
Deep-water systems consist of depositional elements, which are hierarchically organized 80
(e.g. Mutti and Ricci-Lucchi, 1972; Mutti, 1985; Mutti and Normark, 1987; Clark and Pickering, 81
1996; Sprague et al., 2002; Deptuck et al., 2008; Prélat et al., 2009; Di Celma et al., 2011) , the 82
organization of which controls the overall size and connectivity of a reservoir. Architectural 83
elements are determined by their size, architecture, bounding surfaces, and relationship to other 84
architectural elements (e.g. Miall, 1985; Mutti and Normark, 1987; Clark and Pickering, 1996; 85
Sprague et al., 2002; Prélat et al., 2009). Individual depositional facies have variable grain-scale 86
textures, and therefore the spatial arrangement of these depositional facies within an architectural 87
element will determine reservoir potential distribution at that hierarchical level. The stacking of 88
architectural elements and their inherited grain-scale texture allows prediction of reservoir quality 89
at higher levels in the architectural hierarchy. Therefore, understanding facies distribution and 90
grain-scale character is critical to improved prediction of reservoir distribution. Previous 91
publications related to the integration of architectural- and grain-scale observations typically 92
consider broad proximal-to-distal trends, or consider facies variability with limited spatial control 93
(Hirst et al., 2002; Lien et al., 2006; Njoku and Pirmez, 2011; Kilhams et al., 2012; Marchand et al., 94
2015; Porten et al., 2016). Geochemical and mineralogical variations have been recognized within 95
a deep-water channel complex and attributed to the primary texture (Aehnelt et al., 2013). 96
However, no published work has attempted to constrain the depositional reservoir quality within 97
a single architectural element. To assess this issue the following research questions will be 98
addressed: 1) How can an architectural element be characterized at grain-scale? 2) How does 99
reservoir potential vary spatially within an individual architectural element? 3) How do sediment 100
gravity flow processes influence depositional reservoir quality and its distribution? 101
2.1 Geological setting 102
During the Early Eocene the Aínsa-Jaca Basin developed as an east-west trending, 103
southward migrating foredeep (Puigdefàbregas et al., 1975; Mutti, 1984; Labaume et al., 1985; 104
Mutti, 1985; Mutti et al., 1988; Muñoz, 1992; Teixell and García-Sansegundo, 1995). The deep-105
water deposits form the Hecho Group (Fig. 2; Mutti, 1985). The Aínsa Basin fill predominantly 106
consists of submarine slope channel systems and mass-transport deposits, separated by marlstones 107
(e.g. Mutti, 1977; Clark et al., 1992; Mutti, 1992; Clark and Pickering, 1996; Remacha et al., 2003; 108
Pickering and Corregidor, 2005; Moody et al., 2012; Dakin et al., 2013; Bayliss and Pickering, 2015). 109
The Gerbe System (Fig. 2) is interpreted as a canyon to lower-slope channel system (Mutti, 1992; 110
Clark and Pickering, 1996), and consists of: 1) a lower unit that comprizes conglomerate lags, 111
which is interpreted as sediment bypass-dominated; and 2) an upper unit that comprizes fining-112
upward channel-fill elements and records the aggradation and shutdown of the channel system 113
(Mutti, 1992). This study analyzes one channel-fill element from the upper unit. 114
The Jaca Basin succession, which is separated from the exposed part of the Aínsa Basin by 115
the Boltaña Anticline, is interpreted as a series of submarine fans, consisting of lobes and basin-116
plain deposits (Fig. 2; Mutti, 1977; Mutti, 1992; Remacha et al., 2005; Bell et al., in press). The 117
stratigraphy of the basin-fill is constrained by nine regionally mapped ‘megabeds’ (Rupke, 1976; 118
Labaume et al., 1987; Rosell and Wiezorek, 1989; Payros et al., 1999). 119
120
121
122
Figure 2: Stratigraphy and geological setting of the Aínsa-Jaca Basin fill. Regional depositional dip is from 123
right to left, with tentative correlation across the Boltaña anticline following Das Gupta and Pickering 124
(2008). 125
The lobe component of this study focuses on the Upper Broto System, immediately 126
underlying the MT-4 megabed (see also: Mutti, 1992). The Upper Broto is interpreted as proximal 127
lobes (Mutti, 1992; Bell et al., in press), with distal hybrid bed dominated packages where 128
depositional architecture is interpreted to have been influenced by topography ( Remacha and 129
Fernández, 2003; Remacha et al., 2005 Bell et al. in press;). 130
3.1 Methods 131
Different stratigraphic correlations between the Aínsa and Jaca Basins have been proposed 132
(Mutti, 1984; Mutti, 1985; Mutti, 1992; Remacha et al., 2003; Das Gupta and Pickering, 2008; Caja 133
et al., 2010; Clark et al., 2017). Following Das Gupta and Pickering (2008), the Gerbe (Aínsa) and 134
Broto (Jaca) Systems are considered as broadly equivalent and are studied here. Whilst uncertainty 135
remains with this correlation, the two systems form part of the genetically related wider basin-fill, 136
have the same burial history, and, for the puposes of this study, are comparable. Furthermore, 137
linked channel-fills and lobes may accumulate diachronously (e.g. Hodgson et al., 2016), and 138
challenges in correlating individual channel-fills with individual lobes at outcrop mean that 139
sampling the exact time-equivalent stratigraphy may not be possible. One channel-fill element and 140
one lobe were selected from the outcrops to be studied in detail. Detailed sedimentary logs and 141
thin-section analysis were used to investigate spatial changes in architecture, facies and grain-scale 142
texture within the channel-fill and lobe. 143
In the subsurface, reservoir intervals are typically sampled by core plugging at regular intervals, 144
and are biased towards sandstone. These sampling protocols are not designed to capture variability 145
at the architectural element scale. An alternative approach is to sample beds that conform to the 146
mean average bed thickness in an architectural element. However, this would preferentially select 147
thinner beds, which are more common than medium- or thick-bedded sandstone, but typically 148
account for a smaller proportion of the overall sandstone content. Therefore, to characterize an 149
architectural element at grain-scale a repeatable ‘stratigraphic sampling’ method was developed to 150
sample an ‘average’ bed characteristic of the sampled succession (Fig. 3). The method is as follows: 151
a logged section through an architectural element was sub-divided into three sections or ‘windows’ 152
of equal thickness (steps 1 and 2, Fig. 3). Where a window boundary fell within a bed, the boundary 153
was moved to the closest base or top of the nearest sandstone bed. The proportion of sandstone 154
that the thickest and thinnest beds constituted in a window was calculated (step 3, Fig. 3). An 155
average of the two was taken and converted back to a thickness (step 3 Fig. 3). The bed with a 156
thickness that most closely corresponded to this calculated thickness was chosen to be sampled as 157
an ‘average bed’ for the succession (step 4, Fig. 3). A sample of the selected bed was collected from 158
the center of the bed, to avoid the coarse-grained base or fine-grained top. Sampling was designed 159
to assess sedimentary process controls on the depositional reservoir quality of sandstones within 160
architectural elements. Therefore, the texture of non-reservoir facies (e.g. mudstones) were not 161
studied. However, the effects of these potential barriers to flow are considered in architectural 162
element scale analysis. 163
164
Figure 3: The workflow for a repeatable stratigraphic sampling method. Vertical scale in meters. 165
166
Thin-sections were point-counted using a petrographic microscope at 300 points per section 167
(step 5, Fig. 3). The Gazzi-Dickinson method was used to determine composition (Gazzi, 1966; 168
Dickinson, 1970; Ingersoll et al., 1984). The grain-size was determined by measuring the long axes 169
of optically distinguishable grains. The median and D90 (90 th percentile) grain-sizes are used for 170
analysis as mean results were skewed by mudstone chips in some samples. Sorting was determined 171
following Folk and Ward (1957) by measurement of the long and short axis of optically resolvable 172
detrital grains. Detrital and authigenic clays were not distinguishable in thin-section; therefore, 173
there is some uncertainty in inferring initial detrital clay contents. However, it is recognized that 174
proportions of detrital matrix content in modern turbidites is variable between different bed-types 175
(Sumner et al., 2012; Stevenson et al., 2014a; Stevenson et al., 2014b). Thinner-bedded, finer-176
grained distal deposits have higher detrital matrix contents compared to comparatively thicker-177
bedded, coarse grained deposits (Stevenson et al., 2014a; Stevenson et al., 2014b). As the clay 178
content and trends are similar to those observed here the total clay proportion is likely to be a 179
good indicator of original detrital clay content. 180
4.1 Facies 181
Lithofacies are summarized in Table 1 and grouped into facies associations in Table 2:182
Table 1: Lithofacies observed in the study area
Facies Lithology Sedimentology Thickness
(m)
Interpretation Facies code
Mudstone Silty claystone and clayey siltstone Massive- to weakly-laminated. 0.01 – 2.5 Background sedimentation or
deposition from a dilute flow.
LF1
Ripple laminated
sandstone
Coarse-siltstone to fine-
sandstone, rarely medium-
sandstone.
Ripple cross-lamination, typically located in
the upper parts of the bed. Climbing ripples
locally observed. Commonly produces
wavy bed tops.
0.02 – 0.1 Traction plus fallout from a turbulent
flow (Allen, 1982; Southard, 1991;
Mutti, 1992).
LF2
Planar-laminated
sandstone
Very fine- to medium-sandstone. Laminated sandstone with 0.1 m – 1mm
scale alternating coarser – finer laminae.
Laminae are typically parallel, rarely sub-
parallel. Common coarse-tail grading.
Infrequent occurrence of plant fragments
and mudstone chips aligned with laminae.
0.04 – 0.5 Layer-by-layer deposition from
repeated development and collapse
of near-bed traction carpets (Sumner
et al., 2008) and migration of low-
amplitude bed-waves (Best and
Bridge, 1992; Sumner et al., 2008).
LF3
Structureless
sandstone
Very fine- to medium-sandstone,
rare coarse-sandstone.
Typically structureless and commonly
normally-graded or coarse-tail graded.
Occasional mudstone chips occur, typically
in fine- to coarse-sandstone beds.
Nummulites are infrequently observed.
0.05 – 0.5 Rapid settling from a high
concentration flow under hindered
settling conditions (e.g. Sanders,
1965; Lowe, 1982; Mutti, 1992).
LF4
Mm-spaced
laminated
sandstone
Medium- to coarse-sandstone. Laminated sandstone, laminae are 5 – 15
mm thick, parallel to sub-parallel and
typically coarser-grained than surrounding
sandstone. Coarser laminae are typically
inversely graded.
0.1 – 0.5 Repeated collapse of traction carpets
below a high-density turbidity current
(e.g. Mutti, 1992; Cartigny et al.,
2013), or kinetic sieving within the
traction carpet (e.g. Talling et al.,
2012).
LF5
Cross-bedded
sandstone
Medium- to very coarse-sandstone Centimeter- to decimeter-scale cross
stratification. Foresets commonly contain
clasts of mudstone or detrital material, with
maximum grain-sizes of approximately 20
cm. The size of clasts reduces vertically up
0.4 – 0.65 Bed reworking by long-lived flows
with relatively low depositional rates
and near-bed concentrations which
bypassed basin-ward (Allen and
Friend, 1976; Mutti, 1992; Baas et al.,
LF6
foresets. Transition gradually to planar
laminated sandstone over 5 – 10 cm at the
top.
2004; Baas et al., 2011; Talling et al.,
2012).
Conglomerate Poorly sorted clasts of pebbles and
cobbles, with infrequent boulders
(max. 36 cm). Poorly sorted
sandstone matrix.
Clast supported structureless deposit.
Often subtle grading is present in the upper
30 cm. Clasts are usually sub- to well-
rounded and include lithic fragments,
quartz, limestone, mudstone and flint.
0.35 – 1.3 Deposition from a highly
concentrated flow under hindered
settling conditions (e.g. Walker, 1975;
Lowe, 1982), or frictional freezing
(Mutti, 1992).
LF7
Matrix-supported
chaotic deposits
Poorly-sorted, clast-rich matrix
consisting of sandstone, siltstone
and mudstone.
0.2 – 25 0.2 – 25 Clast-rich, poorly-sorted, matrix
supported beds are suggestive of en-
masse deposition from laminar
(debris) flows with a high yield
strength (e.g. Nardin et al., 1979).
LF8
Table 2: Facies associations observed in the study area
Facies
association
Description Interpretation
FA1 An overall thinning- and fining-upwards succession 7 – 9 m thick which
fill a basal incision surface. Characterized by: LF8 at the base overlain by
interbedded LF2 and LF1; a sharp erosive contact to amalgamated LF7;
a sharp, erosive contact to thick-bedded, amalgamated LF3, LF4 and
LF6 containing abundant mudstone chips and lithic-fragments derived
from LF7; a thinning- and fining-upward succession of thin-bedded,
non-amalgamated LF3 and LF2.
Overall thinning- and fining-upward succession filling an
incision is consistent with channel axis deposits (e.g. Mutti,
1977; Clark and Pickering, 1996; Campion et al., 2000; Sullivan
et al., 2000; Beaubouef, 2004; McHargue et al., 2011; Hubbard
et al., 2014; Li et al., 2016).
FA2 Thin-bedded and non-amalgamated LF3 and LF2 0.3 – 1.5 m thick. LF8
may be locally present at the base of the association. Beds are
predominantly tabular and pass laterally into FA1.
Thin-bedded deposits which are adjacent to, and pass into,
thicker –bedded deposits of FA1. Consistent with channel
margin deposits described elsewhere (Mutti, 1977; Clark and
Pickering, 1996; Campion et al., 2000; Eschard et al., 2003;
Beaubouef, 2004; Hubbard et al., 2014; Li et al., 2016).
FA3 Commonly amalgamated packages of LF4 and LF3, with localized LF5,
4 – 6 m thick. Localized scouring on a centimeter- to meter-scale,
however bed geometries are typically tabular over 10’s – 100’s meters.
Thick-bedded, structureless, laterally extensive beds which
transition to thinner-bedded deposits on a 0.1 – 1 km scale and
form packages several meters in thickness are consistent with
lobe axis deposits (Prélat et al., 2009; Grundvåg et al., 2014;
Marini et al., 2015).
FA4 Interbedded, infrequently amalgamated medium- and thin-bedded LF3
and LF2 packages 4 – 6 m thick. LF4 is infrequently observed. Beds
typically have a sharp base and sharp top overlain by LF1. Localized,
decimeter-scale scouring is observed, however beds are predominantly
tabular at outcrop-scale.
Medium- and thin-bedded structured sandstones deposited
predominantly from low-density turbidity currents which form
meter-scale packages are consistent with lobe off-axis deposits
(e.g. Prélat et al., 2009).
FA5 Thin-bedded sandstone and siltstone packages 1 – 2.5 m thick
dominated by LF2 and interbedded with LF1. LF3 is infrequently
observed. Amalgamation is rare. Beds typically exhibit a sharp base, and
sharp top overlain by LF1. Bed geometries are tabular to wavy.
Thin-bedded, rippled, sandstones deposited by dilute low-density
turbidity currents are commonly identified in lateral lobe fringe
deposits (e.g. Prélat et al., 2009; Grundvåg et al., 2014; Marini et
al., 2015; Kane et al., 2017; Spychala et al., 2017b). Similar facies
in the Jaca Basin have previously interpreted as lobe-fringe by
Mutti (1977).
5.1 Architectural element interpretations 189
The geometrical relationships established in the stratigraphic correlations of Figures 4 190
and 5, and the facies associations described in Table 2, are used to interpret the environment of 191
deposition of the Gerbe and Broto architectural elements. 192
193
Figure 4: Architectural panel of the Gerbe channel-fill element (channel-fill element 1 of this complex). The 194
orientation is broadly across depositional strike based on geometry and paleocurrent analysis. The channel-195
form is defined by a major basal erosion-surface. This is overlain by a debrite attributed to channel-196
excavation. The channel-fill has two main facies associations, FA1 and 2. The channel axis, FA1, is 197
characterized by an overall thinning- and fining-upwards succession overlying LF8. The channel margins, 198
FA2, are characterized by thin-bedded low-density turbidites. 199
5.2 Gerbe architectural element 200
The Gerbe channel-fill element is approximately 150 m wide, representing a near complete 201
across depositional-strike transect as indicated by paleocurrent measurements (Fig. 4), and exhibits 202
marked lateral facies changes between log localities (Fig. 4). The measured sections at localities 203
(localities refer to measured sections herein) Gerbe 2 and Gerbe 3 are 8.5 m and 7.9 m thick 204
respectively and are characterized by FA1 (Figs. 4, 6B and D). The Gerbe 1 and Gerbe 4 localities 205
are 1.4 m and 1.1 m, respectively, and are characterized by FA2 (Figs. 4, 6A). 206
5.3 Broto architectural element 207
The Broto lobe (Lobe 1 of Bell et al., in press; Fig. 5), has a comparatively tabular geometry 208
and is approximately 16 km in length and more than 0.9 km wide (Fig. 5A, B). The element exhibits 209
more-gradual lateral facies changes compared to the Gerbe channel-fill element (Fig. 5A, B). The 210
base and top of the architectural element are marked by a debrite (Figs. 5D, 6E) and a laterally 211
persistent thin-bedded package that can be correlated on a kilometer-scale between outcrops (Fig. 212
6G), respectively. The Fanlo 1, Fanlo 2 and Fanlo Track localities predominantly consist of FA3, 213
and are interpreted as lobe axis deposits (Fig. 5, 6E; e.g. Prélat et al., 2009). The A Lecina, Oto and 214
Linás de Broto localities are characterized by FA4 and are interpreted as lobe off-axis (Fig. 6F; e.g. 215
Prélat et al., 2009). The Yésero locality consists of FA5 and is interpreted as the lobe fringe (Fig. 216
6H; e.g. Prélat et al., 2009). The observed facies changes and geometries are consistent with lobes 217
observed elsewhere (e.g. Prélat et al., 2009; Grundvåg et al., 2014; Marini et al., 2015; Kane et al., 218
2017; Spychala et al., 2017a), and have previously been interpreted as lobes within the Jaca Basin 219
(Mutti, 1977; Mutti, 1992; Bell et al., in press). 220
221
Figure 5: Architectural panels of Lobe 1 of the Upper Broto system: A) Depositional-dip correlation of 222
Lobe 1, from lobe axis at Fanlo 2 to frontal lobe fringe at Yésero; B) Depositional-strike architecture of 223
Lobe 1, from lobe axis at Fanlo 1 and Fanlo Track to lobe off-axis at A Lecina; C) Paleocurrents measured 224
in Lobe 1 suggest flow to the northwest, consistent with other studies within the basin (e.g. Mutti 1977, 225
1984, Remacha et al., 2005, Bell et al., in press); D) Stratigraphic context of down depositonal-dip correlation 226
panel showing Lobe 1 in relation to key marker beds (modified from Bell et al., in press.). 227
Gradual facies changes over 100’s – 1000’s meters in Lobe 1 contrast to distal deposits of 228
the Upper Broto System (i.e. the basin plain, sensu Remacha et al., 2005). Northwest of Jaca (Fig. 229
1A) basin-plain deposits exhibit more tabular cross-sectional geometries, with less lateral 230
variability, and do not form lobes (Remacha and Fernández, 2003; Remacha et al., 2005; Bell et al., 231
in press). An idealized basin-plain bed comprizes: a clean basal sandstone, overlain by a clast-rich, 232
poorly-sorted division, followed by a thick mudstone cap with an upper-carbonate-rich division 233
(Remacha and Fernández, 2003; Remacha et al., 2005; Bell et al., in press). Bases of basal clean 234
sandstone divisions have flute and tool marks suggesting flow to the west/northwest. Upper 235
surfaces of some sandstone beds have ripple cross laminations suggesting paleoflow to the north, 236
interpreted to form due to flow deflection from the southern, carbonate slope (Remacha and 237
Fernández, 2003; Remacha et al., 2005; Bell et al., in press). Poorly sorted divisions are interpreted 238
to form either through: repeated deposition and liquefaction of lamina from bores within deflected 239
turbulent flows (Remacha and Fernndez, 2003, Remacha et al., 2005); or from turbulent flows 240
which collapsed to form predominantly laminar flows during flow deflection (Bell et al., in press). 241
6.1 Results 242
Architectural and textural data were collected for both the channel-fill element and lobe. Textural 243
properties are split into facies associations for each architectural element to enable comparison of 244
architectural and textural properties, and consequent depositional reservoir quality in different sub-245
environments within deep-water systems. 246
247
248
Figure 6: A) Channel-margin facies: structured sandstones and siltstones deposited from low-density 249
turbidity currents; B) Channel-axis facies, from the base: pebbly mudstone, conglomerate and cross-bedded 250
sandstone. The cross-bedded sandstone has an erosional base and overlies the conglomerate, with evidence 251
for substrate entrainment; C) Channel-margin siltstones overlying pebbly-mudstone; D) Channel-axis 252
pebbly-mudstone erosively overlain by thick-bedded sandstone; E) Amalgamated, thick-bedded lobe axis 253
sandstones. Onlap of beds onto the underlying debrite is observed to the right of the hammer (length 28 254
cm); F) Medium-bedded lobe off-axis; G) Thin-bedded package overlying Lobe 1 at Fanlo 2. Top of Lobe 255
1 is at the base of the hammer; H) Thin-bedded lobe-fringe sandstones and siltstones at Yésero. 256
6.2 Composition 257
6.2.1 Siliciclastic detrital grains 258
Non-carbonate detrital grains consist of: monocrystalline quartz (6% – 23.7%), polycrystalline 259
quartz (up to 4.3%), plagioclase feldspar (up to 14.3%), K-feldspar (trace), sedimentary rock 260
fragments (up to 3.3%), metamorphic rock fragments (up to 3.7%), igneous rock fragments (up to 261
3.7%), muscovite (up to 1.3%) and trace minerals. 262
6.2.2 Carbonate detrital grains 263
Carbonate grains are common and can make up the largest group of detrital grains within a 264
sample (6.3 – 27.3%). Carbonate grains consist of dolostone, sparitic limestone, micritic limestone, 265
peloids, aggregate grains and fossils. Fossils identified in thin section include foraminifera (benthic 266
and planktonic), gastropods, algae and echinoderm fragments. 267
6.2.3 Authigenic minerals 268
Calcite is the dominant authigenic mineral within the samples (19.7% – 38.3% of grains 269
counted), present as both pore-filling cement and replacement of detrital grains. Minor amounts 270
of authigenic quartz (typically <5%, but locally up to 12%) are identified, typically as overgrowths 271
or pore-filling cement. Traces of authigenic plagioclase and oxide minerals are present, typically 272
<1%. 273
6.2.4 Matrix minerals 274
Matrix-mineralogy is not optically resolvable. However, where present, matrix is typically 275
identified between or coating larger grains. Pseudomatrix consisting of ductile grains (typically 276
mudstone or micritic limestone) is commonly observed within samples. 277
6.2.5 Classification 278
A standard ternary plot of quartz-feldspar-lithic fragments indicates that most samples are 279
categorized as sublitharenites (Fig. 7; see also: Das Gupta and Pickering, 2008; Caja et al., 2010). 280
Linked channel and lobe deposits are shown to exhibit compositional differences (e.g. Stalder et 281
al., 2017). Here, Gerbe samples are more quartz-rich, with some classified as quartz arenites, 282
whereas Broto samples are more feldspar-rich (Fig. 7). This study primarily concerns textural 283
properties and trends, and so composition is not discussed in depth. Compositional evolution, 284
classification and provenance within the Hecho Group are reported in Fontana et al. (1989), Zuffa 285
et al. (1995), Das Gupta and Pickering, (2008), and Caja et al. (2010). 286
287
Figure 7: QFL (Quartz, Feldspar, Lithic fragments) plots from the 36 point-counted thin-sections, assigned 288
to each study area. Most samples are classified as sub-litharenites. However, the Gerbe samples are typically 289
more quartz-rich and feldspar-poor compared to Lobe 1 samples. Ternary plot after Pettijohn et al. (1972). 290
291
Table 3: Architectural and textural properties at each logged section. 292
Basin Locality Net
sandstone
thickness (m)
Sandstone
%
%Amalgamate
d
Median grain-
size (mm)
D90
(mm)
Sorting
(F&W)
Mean matrix% Mean
authigenic
%
Aínsa Gerbe 1 0.425 31.3 14.286 0.090 0.127 0.225 25.675 31.900
Aínsa Gerbe 2 3.360 39.3 15.385 0.098 0.161 0.181 19.633 39.467
Aínsa Gerbe 3 3.680 46.5 39.394 0.109 0.155 0.205 14.433 47.667
Aínsa Gerbe 4 0.040 3.6 0.000 0.041 0.053 0.245 34.333 36.900
Jaca Fanlo 2 5.510 90.0 78.378 0.150 0.212 0.204 7.556 36.111
Jaca Fanlo 1 3.100 77.1 67.742 0.175 0.285 0.134 8.556 31.222
Jaca Oto 2.895 68.9 38.095 0.096 0.141 0.188 15.778 35.889
Jaca Linás de
Broto
3.220 73.7 34.091 0.166 0.316 0.199 15.833 33.417
Jaca Yésero 2 1.385 54.1 3.636 0.056 0.079 0.174 29.000 32.444
Jaca A Lecina 3.945 67.3 28.571 0.169 0.235 0.208 15.444 36.333
Table 4: Architectural and textural properties of facies associations 293
Basi
n
Sub-
environment
Avg. sandstone
thickness (m)
Avg.
sandstone
%
Avg.
%amalgamated
Avg. median
grain-size
(mm)
Avg.
D90
(mm)
Avg.
sorting
(F&W)
Avg.
mean
matrix%
Avg. mean
authigenic
%
Aínsa Channel-axis 3.520 42.9 27.389 0.103 0.158 0.193 17.033 43.567
Aínsa Channel-
margin
0.233 17.4 7.143 0.065 0.090 0.235 30.004 34.400
Jaca Lobe axis 3.453 81.1 69.540 0.192 0.289 0.170 8.181 35.078
Jaca Lobe off-axis 3.353 70.0 33.586 0.143 0.230 0.198 15.685 35.213
Jaca Lobe fringe 1.385 54.1 3.636 0.056 0.079 0.174 29.000 32.444
294
Jaca Fanlo
Track
1.750 76.1 62.500 0.250 0.369 0.173 8.433 37.900
6.3 Gerbe Channel-fill element 295
6.3.1 Architectural- and bed-scale data 296
The thickness of the Gerbe channel-fill element increases from Gerbe 1 and 4 to Gerbe 2 297
and 3 respectively (Fig. 4). The proportion of amalgamated sandstone beds is similar between the 298
channel-margin at Gerbe 1 and channel-axis at Gerbe 2; however, the amalgamation ratio is higher 299
at Gerbe 3, and lower at Gerbe 4 (Figs. 8B; Tables 3, 4). Sandstone-percentage is similar in the 300
channel-axis and channel-margins due to the debrite located in the channel-axis, however the total 301
thickness of sandstone is greater in the channel-axis (Fig. 8B; Table 4). 302
6.3.2 Lateral variation in texture 303
Grain-size varies within the channel-fill sandstones (Figs. 8A, 9; Table 3). The median 304
grain-size slightly increases from the western channel-margin Gerbe 1, into the channel-axis 305
deposits of Gerbe 2 and 3 (440 µm/km; Figs. 8A, 10; Table 3). Median grain-size then decreases 306
to the eastern channel-margin at Gerbe 4 (1130 µm/km; Fig. 8A; Table 3). The D90 (90th percentile 307
of grain-size) shows a similar trend, increasing from Gerbe 1 to Gerbe 2 and 3 (1700 µm/km; Figs. 308
8A, 10; Table 3). The D90 at Gerbe 4 is finer than in other positions (Fig. 8A; Table 3). The 309
optically-resolvable detrital grains of the channel-margin deposits are better sorted compared to 310
the channel-axis deposits (Fig. 8A Table 3). The authigenic mineral content increases from the 311
channel-margins into the channel-axis positions (Fig. 8B; Table 4). Channel-margin deposits at 312
Gerbe 1 and 4 have higher matrix content compared to channel-axis deposits at Gerbe 2 and 3 313
(Fig. 8B; Tables 3, 4). Matrix content increases from Gerbe 2 to 1, and Gerbe 3 to 4 at a rate of 314
310 %/km and 340 %/km respectively (Fig. 10). 315
316
Figure 8: Spatial variation in textural and architectural properties within Lobe 1 and the Gerbe channel-fill 317
element. 318
319
320
Figure 9: Example grain-scale textures of lithofacies: A) High-density turbidite from lobe axis setting; B) 321
High-density turbidite from lobe axis setting. A foram test is present at the top of the sample; C) Low-322
density turbidite from lobe off-axis setting; D) Low-density turbidite from lobe off-axis setting; E) Low-323
density turbidite from lobe fringe setting; F) Channel-axis conglomerate, with large fine-grained dolostone 324
clast; G) Low-density turbidite from channel-axis setting; H) Ripple cross-laminated low-density turbidite 325
from channel-margin setting; I) High-density turbidite from channel-axis setting. 326
327
328
6.3.3 Vertical textural variation 329
Textural properties also vary vertically within the Gerbe channel-fill element (Figs. 9, 11). 330
Overlying the basal debrite, channel-axis deposits show an increase in grain-size (both median and 331
D90) from thin-beds (>4 m on Figs. 11A, B) into the thicker-bedded, amalgamated conglomerate 332
and sandstone (2 – 4 m on Figs. 11A, B). There is a fining upward profile into the thinner-bedded 333
deposits in the upper 2 m (Figs. 11A, B). Channel-margin positions show a general fining upward 334
trend in both median and D90 grain-sizes (Figs. 11A, B). Sorting improves upwards in both 335
channel-axis and channel-margin deposits (Fig. 11B), a decrease in sorting at 5.2 m at Gerbe 2 is 336
observed within the conglomerate sample. There is no clear trend to vertical variation in authigenic 337
mineral content, however an upward decrease is observed at Gerbe 1 (Fig. 11D). There is a general 338
upward increase in matrix content at all positions (Fig. 11E). At channel-axis positions matrix 339
content decreases from the lower thin-bedded deposits into the thick-bedded amalgamated 340
sandstones located between 2 and 4 m (Fig. 11E). Matrix content then shows a general increase 341
upwards into the overlying thinner-bedded deposits (Fig. 11E). 342
6.4 Lobe 1 343
6.4.1 Architectural data 344
The thickness of Lobe 1 decreases from 6.1 m in the most proximal position (Fanlo 2) to 345
2.6 m in the most distal position (Yésero; Fig. 5A). Thickness increases across depositional strike 346
from Fanlo 1 to the lobe off-axis position of A Lecina (Fig. 5B). The proportion of amalgamated 347
beds decreases down-dip from Fanlo 2 to Yésero (4.5%/km; Figs. 8D, 10; Table 3), and across 348
strike from Fanlo 1 to A Lecina (Fig. 8F; Table 3). The degree of amalgamation higher in lobe axis 349
deposits compared to lobe off-axis and lobe fringe deposits (Fig. 8D; Table 4). Sandstone-350
percentage decreases from Fanlo 2 to Yésero (2.8%/km; Figs. 8D, 10; Table 3). Across-strike, the 351
sandstone-percentage decrease from Fanlo 1 to A Lecina is l 352
ess pronounced (Fig. 8F; Table 3). Lobe axis deposits exhibit a higher sandstone 353
proportion than lobe off-axis and lobe fringe deposits (Table 4). 354
355
356
Figure 10: Schematic illustration of the spatial variation in architectural and textural properties within deep-357
water channel-fill elements and lobes. Within the lobe, textural and architectural properties vary most-358
strongly laterally. The channel-fill element shows strong trends in textural and architectural properties both 359
laterally and vertically. The inferred reservoir quality decreases from lobe axis to lobe fringe, and from 360
channel-axis to channel-margin. Reservoir quality also decreases vertically within the Gerbe channel-fill 361
element, if the basal non-reservoir debrite is not included. The lateral gradient of change in properties is 362
typically around two orders of magnitude greater within the channel-fill element compared to the lobe. 363
364
6.4.2 Textural data 365
Textural properties vary spatially within Lobe 1 (Figs. 8C and E, 9; Table 3). Overall, 366
median grain-sizes decrease down-dip from Fanlo 2 to Yésero (6 µm/km; Figs. 8C, 10; Table 3). 367
Across strike, median grain-size decreases from Fanlo 1 and Fanlo Track, to A Lecina (Fig. 8E; 368
Table 3). The D90 decreases down-dip from Fanlo 2 to Yesero (5 µm/km; Figs. 8A, 10; Table 3). 369
D90 increases northwards, across strike from Fanlo 1 to Fanlo Track, but is lower at A Lecina 370
(Fig. 8E; Table 3). In both measurements of grain-size, there is a down-dip increase from Oto to 371
Linás de Broto (Fig. 8C; Table 3). Sorting is relatively consistent throughout Lobe 1, with most 372
samples categorized as moderately or moderately-well sorted (Figs. 8C, E; Table 3; sensu Folk and 373
Ward, 1957). 374
The proportion of authigenic minerals shows little variation across Lobe 1 (Fig 8D, F; 375
Table 3). Positions with the highest authigenic mineral contents are in proximal areas (Fanlo 2, 376
Fanlo Track, A Lecina, and Oto; Figs. 8D, F; Table 3); however, Fanlo 1 has the lowest authigenic 377
mineral content (Figs. 8D, F; Table 3). The proportion of matrix increases down-dip from Fanlo 378
2 to Yésero (Fig. 8D; Table 3). Matrix content also increases across-strike from Fanlo 1 to A Lecina 379
(Fig. 8F; Table 3). 380
Lobe axis deposits exhibit the coarsest median grain-sizes compared to lobe off-axis and 381
lobe fringe deposits (Figs. 8C and E, 9; Table 3); and coarser D90 grain-sizes compared to lobe 382
off-axis deposits (Figs. 8C and E, 12B and C; Table 3). The lobe fringe has a much lower D90 383
(Figs. 8C, 12B and C; Table 3). Sorting increases from lobe axis deposits into lobe off-axis deposits, 384
and decreases from lobe off-axis deposits into the lobe fringe deposits (Figs. 8C and E, and 12C 385
and D; Table 4). 386
Lobe axis and lobe off-axis deposits exhibit marginally higher contents of authigenic 387
minerals than the lobe fringe deposits (Fig. 12A; Table 4). Lobe axis deposits exhibit the lowest 388
matrix contents, lobe off-axis deposits have medial matrix contents, and the lobe fringe deposits 389
have the highest matrix content (Figs. 8D and F, 12A, B and D; Table 4). The rate of change is 390
different between the lobe axis and lobe off-axis, and lobe off-axis and lobe fringe. Matrix content 391
increases at 0.6 %/km between Fanlo 2 and Linás de Broto, compared to 3.8 %/km between Linás 392
de Broto and Yesero (Lobe overall increase is 1.3 %/km; Figs. 8D, 10). 393
6.5 Comparison of textural properties 394
Scatter plots of textural properties suggest channel-margin and channel-axis deposits have 395
different textural characteristics (Fig. 12). Higher proportions of matrix correspond to lower 396
proportions of authigenic minerals in the Gerbe samples (Fig. 12A). Increased matrix content also 397
corresponds to finer grain-sizes and better sorting of detrital grains in the samples (Fig. 12B, C). 398
Decreases in grain-size are associated with improved sorting of detrital grains, and increased matrix 399
content (Fig. 12B, D). Channel-margin deposits (Gerbe 1 and 4) have fine grain-sizes, high 400
proportions of matrix, low proportions of authigenic minerals and better sorting (Figs. 8A and B, 401
12; Table 4). Comparatively, channel-axis deposits exhibit coarser grain-sizes, lower proportions 402
of matrix, higher proportions of authigenic minerals, and are more poorly sorted (Figs. 8A and B, 403
12; Table 4). 404
405
Figure 11: Vertical variation in textural properties at each Gerbe logged section. The top of each section is 406
used as a datum. Grain-size typically decreases upwards within the channel fill (A and B). Within the 407
channel-axis there is an apparent initial increase in grain-size. This is attributed to the upward transition 408
from a package of thin-beds, interpreted as the deposits of the dilute tails of larger flows which bypassed 409
the locality, to the main aggradational-fill of the channel. Sorting increases upwards within the channel-fill 410
(C). The most poorly-sorted sample (~3.2 m Gerbe 2) is a conglomerate (LF6). Vertical changes in 411
authigenic content are not strongly developed (D). The proportion of matrix increases upwards within the 412
channel-fill (E). The initial decrease in the channel-axis represents the transition from the initial bypass-413
phase to the main aggradational-phase of sand deposition. 414
Lobe 1 exhibits a similar separation of textural properties. Increasing matrix content 415
correlates with decreasing grain-size and better sorting (Fig. 12A, B, D). Matrix and authigenic 416
mineral contents do not exhibit a strong relationship (Fig. 12A). Samples with coarser grain-sizes 417
also exhibit poorer sorting compared to samples with finer grain-sizes (Fig. 12C). Separate 418
groupings of lobe axis, lobe off-axis and lobe fringe samples suggests the sub-environments have 419
distinct textural properties (Fig. 12) although this is likely to form part of a continuum. 420
Comparison of channel-fill element and lobe sub-environment deposits shows similarities 421
between the different architectural elements (Fig. 12). Positions dominated by thinner-bedded 422
deposits (channel-margin and lobe fringe) have finer grain-sizes, higher matrix content, are better 423
sorted and have marginally lower authigenic mineral content compared to positions with thicker-424
bedded channel-axis and lobe axis deposits (Fig. 12; Table 4). Channel-axis and lobe off-axis 425
deposits show the greatest range in textural properties (Fig. 12; Table 4), especially in grain-size 426
and matrix content (Fig. 12; Table 4). 427
The rate of change of textural properties is typically around two orders of magnitude more 428
abrupt in the channel-fill element (channel axis to channel margin) in comparison to the lobe (Fig. 429
10). 430
431
432
Figure 12: Variation of textural properties within channel and lobe sub-environments. Samples are grouped 433
by sub-environment interpretations. Channel margin and lobe fringe samples show overlap and consistently 434
have comparatively finer grain-sizes and higher matrix contents. Channel axis and lobe off-axis samples 435
overlap and exhibit a mix of grain-sizes and matrix contents. The lobe axis samples typically plot in a discrete 436
area due to coarser grain-sizes and lower matrix contents. 437
7.1 Discussion 438
7.2 Spatial variation in depositional reservoir quality 439
The distribution of textural properties (grain-size, sorting and matrix content) within architectural 440
elements is a first-order control on the initial depositional porosity and permeability of sandstones 441
(e.g. Fraser, 1935; Beard and Weyl, 1973; Hirst et al., 2002; Lien et al., 2006; Njoku and Pirmez, 442
2011; Kilhams et al., 2012; Marchand et al., 2015; Porten et al., 2016; Southern et al., 2017) and 443
provides insight into the depositional reservoir quality within the study area. The effects of post-444
depositional modification are not discussed unless explicitly stated. 445
7.2.1 Gerbe channel-fill element 446
Textural properties vary both laterally and vertically within the Gerbe channel-fill element 447
(Figs. 8, 9, 10, 11, 12). Grain-size increases and matrix content decreases from channel-margins to 448
channel-axis (Figs. 8, 10, 11, 12). In unconsolidated sand, as grain-size increases pore throats 449
become larger and permeability increases (e.g. Beard and Weyl, 1973). However, changes in grain-450
size do not affect porosity within deposits with the same degree of sorting (Beard and Weyl, 1973). 451
This suggests that initial permeability would have been higher in channel-axis deposits. Grain-size 452
also decreases stratigraphically within the Gerbe channel-fill element (Fig. 11A, B), suggesting 453
initial permeability decreased upwards. Sorting is better in the channel-margins, and also increases 454
vertically within the channel-fill (Figs. 8, 11, 12). Well-sorted deposits exhibit higher porosity and 455
permeability in unconsolidated sand as smaller grains fill intergranular space and block pore throats 456
in poorly-sorted deposits (Beard and Weyl, 1973). However, the overall effect of sorting on 457
reservoir quality is currently inconclusive, as grain-size and clay content often mask its effect (Lien 458
et al., 2006; Porten et al., 2016; c.f. Njoku and Pirmez, 2011). This is likely an artefact of traditional 459
point counting methods, which calculate sorting data from optically resolvable grains (i.e. not 460
clays). Therefore, channel margin and lobe fringe deposits in which hydraulic fractionation resulted 461
in well-sorted detrital grains, but with a high-matrix content, appear well-sorted. In contrast, the 462
deposits of relatively poorly-stratified, high-density flows are likely to have poorer-sorting of 463
detrital grains, but low-matrix contents. High matrix content in channel margin positions (Figs. 8, 464
10, 11, 12) likely reduced both initial porosity and permeability as detrital clay can impact reservoir 465
quality by blocking pore throats and reducing permeability (Fraser, 1935; Hirst et al., 2002; Lien et 466
al., 2006; Porten et al., 2016). Authigenic mineral content is highest in the channel axis (Fig. 8B), 467
suggesting a higher initial porosity, and that fluid flow was greater in these deposits prior to 468
mesodiagenesis, suggesting higher initial permeabilities. 469
Both sandstone-percentage and the proportion of amalgamated beds decrease from 470
channel-margin to channel-axis (Fig. 8B, 10). Therefore, channel-axis deposits exhibit better 471
depositional reservoir quality at both grain-scale (porosity and permeability) and architectural 472
element scale (sandstone-percentage and amalgamation) compared to channel-margin deposits 473
(Fig. 10). 474
Whilst the depositional reservoir quality of channel-axis sandstones is better compared to 475
the channel margin, the channel-axis in this case contains a thick mudstone-rich debrite. This 476
debrite would have poor reservoir properties (e.g. Hirst et al., 2002), and reduce the overall vertical 477
permeability and depositional reservoir quality of the channel axis. However, incision of channel-478
fill element one by channel-fill elements two and three improves vertical connectivity of channel-479
axis sandstones in the channel-complex axis (Fig. 4). 480
481
7.2.2 Process controls on depositional reservoir quality distribution 482
Cycles of channel initiation, incision, and filling record a complicated waxing-waning 483
history of flow energy, and associated sediment bypass and aggradation (e.g. Mutti and Normark, 484
1987; Mutti, 1992; Clark and Pickering, 1996; McHargue et al., 2011; Hubbard et al., 2014; 485
Stevenson et al., 2015). The basal channel surface is interpreted to be excavated by a debris flow, 486
or flows (e.g. Dakin et al., 2013), which deposited the debrite. The debrite is erosively overlain by 487
siltstone and discontinuous thin sandstone beds, interpreted to represent a bypass-dominated 488
channel-base-drape (e.g. Hubbard et al., 2014; Stevenson et al., 2015). Silt-prone drapes act as 489
barriers to flow, but notable detrimental effects are only observed with cross-sectional drape 490
coverages in excess of 60% (e.g. Barton et al., 2010). Subsequent channel-axis aggradation is 491
dominated by amalgamated high-density turbidites (Figs. 4, 13), resulting in high sandstone-492
percentage and connectivity. The fill progressively thins and fines upward into thin-bedded low-493
density turbidites (Figs. 4, 13). Channel-margin deposits are characterized almost exclusively by 494
low-density turbidites (Figs. 4, 13). Topography steers high-density turbidity currents more-495
strongly than low-density turbidity currents (e.g. Al Ja’aidi et al., 2004), and so focussing of high-496
density turbidity currents within the thalweg concentrates the best reservoir properties in the 497
channel-axis (Figs. 10, 13). Low-density flows, or low-density parts of stratified flows, are able to 498
surmount topography, depositing low-density turbidites contemporaneously on the channel-499
margin (Fig. 13A, B; e.g. Hiscott et al., 1997). In later stages of channel aggradation, the channel-500
cut is partly-to-fully filled due to system back-stepping through relative sea-level rise, or other 501
mechanisms, reducing flow-volume and sediment supply to the channel-fill (e.g. Mutti and 502
Normark, 1987; Clark and Pickering, 1996; Campion et al., 2000; Gardner and Borer, 2000; 503
McHargue et al., 2011; Di Celma et al., 2014; Hubbard et al., 2014 ; Hodgson et al., 2016). 504
Reduction of sediment supply and smaller flow-volume means later flows reaching a given location 505
are finer-grained, more-dilute and have poorer reservoir potential compared to earlier 506
aggradational deposits. 507
508
509
Figure 13: Flow process controls on channel-fill reservoir potential. The lower channel-axis is filled 510
by debrites (E), which are poorly-sorted, mudstone-rich and low reservoir potential. Conglomerate (D), 511
representative of a high-concentration, strongly bypassing flow. Reservoir potential in initial channel-axis 512
deposits is high due to amalgamation of high-density turbidites (C and D). Decreases in amalgamation and 513
grain-size, and increases in matrix content vertically and laterally reduce depositional reservoir quality. The 514
upper channel-fill element fill axis (A) and channel-margins (B) are dominated by non-amalgamated low-515
density turbidites and have poorer grain-scale reservoir potential. 516
7.2.3 Lobe 1 517
Within Lobe 1, the decrease in grain-size from lobe axis to lobe fringe positions (Figs. 8C, 9, 10 518
12) suggests that initial permeability decreased away from the lobe axis. The proportion of matrix 519
increases from lobe axis to lobe fringe (Figs. 8C, 12; see also: Hirst et al., 2002; Marchand et al., 520
2015; Kane et al., 2017; Fildani et al., 2018), which suggests the lobe-axis exhibited the highest 521
initial porosity and permeability. Trends in sorting are weak in Lobe 1. Lobe off-axis deposits are 522
generally better sorted than both lobe axis and lobe fringes, and therefore the original porosity 523
may have been higher (Fig. 12C, D). However, as grain-size and matrix content are considered 524
stronger controls on reservoir quality (Hirst et al., 2002; Lien et al., 2006; Porten et al., 2016), they 525
are likely to overprint this parameter. At architectural-element scale, the sandstone-percentage and 526
degree of amalgamation decrease away the from lobe axis to the lobe fringe (90 to 54%and 78.38 527
to 3.64% respectively; Figures 8D and F). This suggests lobe-axes had higher reservoir volume and 528
connectivity. Authigenic mineral content is less variable than in the channel-fill element, but is 529
slightly higher in lobe off-axis and lobe axis (Fig. 8D, F), suggesting increased fluid flow during 530
diagenesis. Lobe axis deposits exhibit the best depositional reservoir quality at both grain- and 531
architectural-scales (Fig. 10). Reservoir potential decreases slightly from lobe axis to lobe off-axis, 532
at grain- and architectural-scale (Fig. 10). The relatively abrupt increase in matrix content, decrease 533
in grain-size, decrease in sandstone-percentage and decrease in amalgamation from lobe off-axis 534
to lobe fringe (over a scale of 3.25 km) suggests that depositional reservoir quality and vertical 535
connectivity within lobes decreases considerably from the lobe off-axis to the lobe fringe (Fig. 10). 536
Where lobe fringe successions are reservoir prospects, they are likely to be challenging due to their 537
(relatively) finer grain-size, increased matrix content, reduced thickness and poorer connectivity 538
compared to more proximal positions (Kane and Pontén, 2012; Marchand et al., 2015; Southern 539
et al., 2017; Fildani et al., 2018). 540
7.2.4 Process controls on depositional reservoir quality distribution 541
Lobes exhibit lateral facies changes that reflect different sub-environments. Lobe axis 542
deposits are dominated by high-density turbidites, lobe off-axis deposits contain a mixture of high- 543
and low-density turbidites and lobe fringe deposits are dominated by low-density turbidites (Figs. 544
5, 14; e.g. Prélat et al., 2009). Lateral variation of textural properties and composition has been 545
observed in experimental studies (e.g. Middleton, 1967; Garcia, 1994; Gladstone et al., 1998; 546
Hodson and Alexander, 2010; Pyles et al., 2013) and in ancient deposits (Fig. 14; e.g. Hirst et al., 547
2002; Kane et al., 2017; Lien et al., 2006; Marchand et al., 2015; Porten et al., 2016; Southern et al., 548
2017; Fildani et al., 2018). Coarse grains are deposited by high-density turbidity currents in 549
proximal positions whereas fines that reach the basin-floor are transported to distal positions in 550
low-density turbidity currents (Fig. 14; e.g. Middleton, 1967). Enrichment of fine-grained material 551
in the lobe fringes may be due to entrainment of substrate in the channel-lobe transition zone, and 552
proximal lobe positions (Kane and Pontén, 2012; Fildani et al., 2018). As grain-size and matrix are 553
strong controls on depositional reservoir quality, their segregation within flow deposits influences 554
reservoir potential distribution within lobes (Figs. 10, 14). 555
556
Figure 14: Illustration of flow-process controls on reservoir potential within lobes. Lobe axis 557
deposits (A) have high reservoir potential as they are dominated by amalgamated high-density turbidites 558
with coarse grain-sizes and low matrix content. Lobe off-axis deposits (B and C) have moderate-to-high 559
reservoir potential as they contain a mixture of high- and low-density turbidites. Low-density turbidites 560
have finer grain-sizes and higher amounts of matrix compared to high-density turbidites, thus reducing 561
their reservoir potential. Lobe-fringe deposits (D) contain abundant non-amalgamated low-density 562
turbidites. Lobe-fringe low-density turbidites have fine grain-sizes and higher matrix content, reducing 563
reservoir potential compared to lobe axis and lobe off-axis deposits. 564
7.3 Implications of detrital matrix distribution 565
Detrital matrix and ductile grains have a negative effect on the depositional reservoir 566
quality by blocking pore throats (e.g. Fraser, 1935), and during compaction by forming a 567
pseudomatrix (e.g. Marchand et al., 2015). However, clay coatings (predominantly chlorite) on 568
grains can also act to preserve porosity and permeability by inhibiting the growth of authigenic 569
quartz (e.g. Heald and Larese, 1974; Ehrenberg, 1993; Bloch et al., 2002; Anjos et al., 2003; Dowey 570
et al., 2012). Authigenic quartz growth is accelerated in basins with higher heat flows (e.g. 571
Walderhaug, 1994), such as the northern Norwegian Sea (e.g. Ritter et al., 2004). In these cases, 572
deposits with higher matrix contents, whilst exhibiting lower initial porosity and permeability, may 573
act to preserve the porosity and permeability present during deeper burial. Consequently, porosity 574
and permeability in architectural element positions with lower matrix contents (e.g. lobe axis) are 575
more likely to be reduced by authigenic quartz growth. A balance of the initial porosity and 576
permeability, and that preserved from authigenic quartz, may favour medial values of grain-size 577
and matrix content in these cases, such as lobe off-axis deposits. However, as temperature and 578
compaction increase with burial the diagenetic overprint control on reservoir quality is likely to 579
become stronger relative to the depositional control (see also: Porten et al., 2016). 580
8.1 Conclusions 581
Two deep-water architectural elements, a channel-fill element and a lobe, are characterized 582
at grain-scale using quantitative methodology to map depositional reservoir quality spatially within 583
individual architectural elements for the first time. Quantification of these data and their rates of 584
change can be important parameters for sub-surface predictability and fluid flow simulation 585
models. Textural and architectural properties show strong spatial variation in both elements. The 586
distribution of initial depositional reservoir quality within, and between sub-environments is 587
controlled by flow processes and their spatial and temporal evolution. 588
Within the channel-fill element, channel-axis deposits have the best depositional reservoir 589
quality as they have the coarsest grain-size and lowest matrix content. However, depositional 590
reservoir quality decreases upwards within the channel-axis, as the proportion of high-density 591
turbidites decreases, and low-density turbidites increases as the channel-fill aggrades. Channel-592
margin deposits consist of low-density turbidites which have low reservoir potential due to their 593
finer grain-sizes and high matrix content. Channel-axis deposits are also more amalgamated, and 594
contain a greater thickness of sandstone, therefore they have better connectivity and volume 595
compared to channel-margin deposits. Lobe axis deposits are dominated by high-density 596
turbidites, which have better depositional reservoir quality compared to the lobe off-axis and lobe 597
fringe as they have the coarsest grain-size, lowest matrix content, most amalgamation and highest 598
net-to-gross. Lobe off-axis deposits contain a mixture of high- and low-density turbidites, giving 599
moderate depositional reservoir quality. Lobe fringe deposits are characterized by low-density 600
turbidites, which have the poorest depositional reservoir quality as they have the finest grain-size, 601
highest matrix content, lowest degree of amalgamation and lowest net-to-gross. The rate of change 602
in grain-size, matrix content and amalgamation increases from lobe off-axis to lobe fringe. This 603
suggests reservoir potential decreases more abruptly from the lobe off-axis into the lobe fringe 604
compared to from the lobe axis to lobe off-axis. However, in basin-fills with high heat-flow, sub-605
environments with increased detrital matrix and clay-coating of grains which inhibit authigenic 606
quartz growth (e.g. lobe off-axis), may preserve initial porosity and permeability post-diagenesis. 607
The studied deep-water architectural elements exhibit similar meso-scale facies, stacking patterns 608
and lithofacies distributions to deep-water systems of different basins, ages and delivery systems. 609
Quantified depositional reservoir quality distribution intimately ties to this predictable facies 610
organisation and should therefore be predictable elsewhere. 611
Acknowledgments 612
The authors are grateful to the AAPG Foundation Grants-In-Aid program for the award of the R. Dana 613
Russell memorial grant, which part-funded this research. We thank Salvatore Critelli for his editorial 614
handling of the paper and the reviews of Salvatore Milli and an anonymous reviewer whose comments 615
enhanced the clarity of the manuscript. 616
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